Diagnosis, choice of treatment, and prognosis of cardiovascular disease are still based on a few biomarkers, such as high blood pressure, cholesterol (LDL/HDL), and triglycerides. While these biomarkers improve clinical practice at population level, their sensitivity and specificity in particular subpopulation groups may be more limited. Because these few risk factors are an extreme oversimplification of a complex physiological condition, where intricate interplay between genetics, environment and lifestyle contributes to the heterogenous landscape of metabolic states. This project aims to investigate and understand the metabolic heterogeneity of cardiovascular disease, develop metabolic scores for better prediction and to devise strategies for better response to lifestyle modifications. We believe that findings of this project will drastically advance understanding of CVD and improve our detection and predictive capabilities for CVD by expanding the scope of current algorithms.

2024

2028